SOTAVerified

Denoising

Denoising is a task in image processing and computer vision that aims to remove or reduce noise from an image. Noise can be introduced into an image due to various reasons, such as camera sensor limitations, lighting conditions, and compression artifacts. The goal of denoising is to recover the original image, which is considered to be noise-free, from a noisy observation.

( Image credit: Beyond a Gaussian Denoiser )

Papers

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Showing 1751–1800 of 7282 papers

TitleStatusHype
Continuous-variable Quantum Diffusion Model for State Generation and Restoration—0
Local Averaging Accurately Distills Manifold Structure From Noisy Data—0
EHCube4P: Learning Epistatic Patterns Through Hypercube Graph Convolution Neural Network for Protein Fitness Function Estimation—0
Exploring Strategies for Personalized Radiation Therapy Part II Predicting Tumor Drift Patterns with Diffusion Models—0
FlowRAM: Grounding Flow Matching Policy with Region-Aware Mamba Framework for Robotic Manipulation—0
Learning Multi-scale Spatial-frequency Features for Image Denoising—0
EDNet: A Distortion-Agnostic Speech Enhancement Framework with Gating Mamba Mechanism and Phase Shift-Invariant Training—0
Generative thermodynamic computing—0
D2Diff : A Dual Domain Diffusion Model for Accurate Multi-Contrast MRI SynthesisCode0
CWGAN-GP Augmented CAE for Jamming Detection in 5G-NR in Non-IID Datasets—0
A Real-time Endoscopic Image Denoising System—0
Fiber Signal Denoising Algorithm using Hybrid Deep Learning Networks—0
Demonstrating Superresolution in Radar Range Estimation Using a Denoising Autoencoder—0
Optimization-Based Image Restoration under Implementation Constraints in Optical Analog Circuits—0
Expressive Score-Based Priors for Distribution Matching with Geometry-Preserving RegularizationCode0
Cost-Aware Routing for Efficient Text-To-Image Generation—0
Iterative Camera-LiDAR Extrinsic Optimization via Surrogate DiffusionCode0
Exploring Diffusion with Test-Time Training on Efficient Image Restoration—0
A Comparative Evaluation of Deep Learning Models for Speech Enhancement in Real-World Noisy Environments—0
DiffusionBlocks: Blockwise Training for Generative Models via Score-Based Diffusion—0
Block-wise Adaptive Caching for Accelerating Diffusion Policy—0
Limited-Angle CBCT Reconstruction via Geometry-Integrated Cycle-domain Denoising Diffusion Probabilistic Models—0
WISVA: Generative AI for 5G Network Optimization in Smart Warehouses—0
GeoRecon: Graph-Level Representation Learning for 3D Molecules via Reconstruction-Based Pretraining—0
Imaging at the quantum limit with convolutional neural networksCode0
Zero-Shot Solving of Imaging Inverse Problems via Noise-Refined Likelihood Guided Diffusion Models—0
Sharpness-Aware Machine Unlearning—0
Evolvable Conditional Diffusion—0
Exploiting the Exact Denoising Posterior Score in Training-Free Guidance of Diffusion Models—0
STAGE: A Stream-Centric Generative World Model for Long-Horizon Driving-Scene Simulation—0
SpeechRefiner: Towards Perceptual Quality Refinement for Front-End Algorithms—0
GM-LDM: Latent Diffusion Model for Brain Biomarker Identification through Functional Data-Driven Gray Matter Synthesis—0
DiffS-NOCS: 3D Point Cloud Reconstruction through Coloring Sketches to NOCS Maps Using Diffusion Models—0
Zero-shot denoising via neural compression: Theoretical and algorithmic frameworkCode0
Constraint-Guided Prediction Refinement via Deterministic Diffusion Trajectories—0
ReFrame: Layer Caching for Accelerated Inference in Real-Time Rendering—0
Cross-Domain Conditional Diffusion Models for Time Series ImputationCode0
Revisiting Transformers with Insights from Image Filtering—0
DiffPR: Diffusion-Based Phase Reconstruction via Frequency-Decoupled Learning—0
High-resolution efficient image generation from WiFi CSI using a pretrained latent diffusion model—0
Contrastive Matrix Completion with Denoising and Augmented Graph Views for Robust RecommendationCode0
Joint Denoising of Cryo-EM Projection Images using Polar Transformers—0
A Deep Generative Model for the Simulation of Discrete Karst Networks—0
Time-Unified Diffusion Policy with Action Discrimination for Robotic Manipulation—0
Diffusion prior as a direct regularization term for FWI—0
Assessing the Quality of Denoising Diffusion Models in Wasserstein Distance: Noisy Score and Optimal BoundsCode0
Text-Aware Image Restoration with Diffusion Models—0
Scalable Non-Equivariant 3D Molecule Generation via Rotational AlignmentCode0
Fast Monte Carlo Tree Diffusion: 100x Speedup via Parallel Sparse Planning—0
How Much To Guide: Revisiting Adaptive Guidance in Classifier-Free Guidance Text-to-Vision Diffusion Models—0
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All datasetsDarmstadt Noise DatasetDIV2KDNDiris

Benchmark Results

#ModelMetricClaimedVerifiedStatus
1SINDyPSNR81—Unverified
2Pixel-shuffling DownsamplingPSNR38.4—Unverified
3TWSCPSNR37.93—Unverified
4CBDNet(Syn)PSNR37.57—Unverified
5MCWNNMPSNR37.38—Unverified
6Han et alPSNR35.95—Unverified
7FFDNetPSNR34.4—Unverified
8TNRDPSNR33.65—Unverified
9CDnCNN-BPSNR32.43—Unverified
10NLRNPSNR30.8—Unverified
#ModelMetricClaimedVerifiedStatus
1DRUnet_Poisson_0.01Average PSNR (dB)33.92—Unverified
#ModelMetricClaimedVerifiedStatus
1DRANetAverage PSNR39.64—Unverified
#ModelMetricClaimedVerifiedStatus
1PCNN+RL+HMEAverage84.61—Unverified